Systems and methods for data entry

ABSTRACT

Systems and methods for entering and storing data. User input defining a data set is received. A data collection construct including a data entry user interface for inputting data in the data set is defined using the user input. A data storage construct including queries for retrieving the data is automatically defined based on the user input. Additional user input indicating modifications to the data set is received. The data collection construct, the data storage construct, and the queries are automatically updated based on the additional user input indicating modifications to the data set.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/877,169, filed Jan. 22, 2018, which claims the benefit under 35U.S.C. § 119(e) of United States Provisional Application Ser. No.62/507,693 filed May 17, 2017, the content of which is incorporated byreference in its entirety into the present disclosure.

FIELD OF THE INVENTION

This disclosure relates to systems and methods for entering data,managing data, tracking data based on user input, retrieving data,and/or modification of data.

BACKGROUND

Under conventional approaches, a platform for entering data is provided.Through platforms provided under conventional approaches, a user has tomanually define each data collection construct for use in collectingdata regardless of whether each data collection construct sharescommonalities or are otherwise related. Specifically, under conventionalapproaches a user has to manually define an entire data collectionconstruct without sharing code commonalities with other data collectionconstructs associated with the data collection construct. Additionally,through platforms provided under conventional approaches, a user has tomanually define each data storage construct for storing data collectedthrough a data collection construct regardless of whether each datastorage construct shares commonalities or are otherwise related.Specifically, under conventional approaches a user has to manuallydefine an entire data storage construct without sharing codecommonalities with other data storage constructs associated with thedata storage construct. Additionally, when data storage constructs,platforms, or data collection constructs change, a user must manuallyredefine the other facets of the system. For example, when the storageconstruct changes, the user has to manually redefine the associatedplatform and the data collection construct.

SUMMARY

Various embodiments of the present disclosure can include systems,methods, and non-transitory computer readable media configured to obtainone or more source code files that correspond to a software program.User input defining a data set can be received. The user input may alsoinclude dependencies of the user defined data set (e.g., defining one ormore behaviors of associated user interfaces). A data collectionconstruct including a data entry user interface for inputting data inthe data set can be defined using the user input. A data storageconstruct including queries for retrieving the data can be automaticallydefined based on the user input. Additional user input indicatingmodifications to the data set can be received. The data collectionconstruct, the data storage construct, and the queries can beautomatically updated based on the additional user input indicatingmodifications to the data set.

In some embodiments, the systems, methods, and non-transitory computerreadable media can be configured to define one or more validationconstraints based on the user input. Data in a data set can beautomatically validated automatically at a data entry user interface asthe data is input into the data entry user interface of a datacollection construct based on the one or more data validationconstraints to determine if the data is valid. An invaliditynotification can be presented to a user through the data entry userinterface indicating the data is invalid if it is determined the data isinvalid.

In some embodiments, the systems, methods, and non-transitory computerreadable media can be configured to select a portion of the data in adata set entered through a data collection construct to transfer to arepository (e.g., a central repository and/or non-central repository).The portion of the data in the data set stored according to a datastorage construct can be transferred to the repository. The data in thedata selected for transfer to the repository can be selected based on asize of the portion of the data in the data set.

In some embodiments, the systems, methods, and non-transitory computerreadable media can be configured to define a data storage constructbased on the user input for defining the data collection construct whilerefraining from querying the user for further input for defining thedata storage construct.

In some embodiments, the systems, methods, and non-transitory computerreadable media can be configured to define a data collection constructusing a previously defined data collection construct.

In some embodiments, the systems, methods, and non-transitory computerreadable media can be configured to define a data storage constructusing a previously defined data storage construct.

In some embodiments, the systems, methods, and non-transitory computerreadable media can be configured to automatically define a data storageconstruct and queries for use in retrieving data stored using the datastorage construct based on the data collection construct using datastorage construct definition rules.

In some embodiments, the systems, methods, and non-transitory computerreadable media can be configured to group a data collection constructwith an already defined data collection construct.

In some embodiments, the systems, methods, and non-transitory computerreadable media can be configured to define a data collection constructincluding a data entry user interface to include a form to collect datain a data set through according to user input indicating the form tocollect the data through.

BRIEF DESCRIPTION OF THE DRAWINGS

Certain features of various embodiments of the present technology areset forth with particularity in the appended claims. A betterunderstanding of the features and advantages of the technology will beobtained by reference to the following detailed description that setsforth illustrative embodiments, in which the principles of the inventionare utilized, and the accompanying drawings of which:

FIG. 1 illustrates an example environment for entering data, inaccordance with various embodiments.

FIG. 2 illustrates an example environment for defining a data collectionconstruct, in accordance with various embodiments.

FIG. 3 illustrates an example environment for defining a data storageconstruct, in accordance with various embodiments.

FIG. 4 illustrates an example environment for selectively transferringdata to a repository, in accordance with various embodiments.

FIG. 5 illustrates a flowchart of an example method, in accordance withvarious embodiments.

FIG. 6 illustrates a block diagram of an example computer system inwhich any of the embodiments described herein may be implemented.

DETAILED DESCRIPTION

Under conventional approaches, a platform for entering data is provided.Through platforms provided under conventional approaches, a user has tomanually define each data collection construct for use in collectingdata regardless of whether each data collection construct sharescommonalities or are otherwise related. Specifically, under conventionalapproaches a user has to manually define an entire data collectionconstruct without sharing code commonalities with other data collectionconstructs associated with the data collection construct. Additionally,through platforms provided under conventional approaches, a user has tomanually define each data storage construct for storing data collectedthrough a data collection construct regardless of whether each datastorage construct shares commonalities or are otherwise related.Specifically, under conventional approaches a user has to manuallydefine an entire data storage construct without sharing codecommonalities with other data storage constructs associated with thedata storage construct.

A claimed solution rooted in computer technology overcomes problemsspecifically arising in the realm of computer technology. In variousembodiments, a user can provide user input for defining a data set. Userinput provided by a user defining a data set can be used in collectingdata for the data set. In certain embodiments, a data collectionconstruct can be defined for collecting data in the data set based onthe user input. The user input can be used to generate and/or update adata entry user interface based on the user input for purposes ofcollecting data in the data set based on the user input. For example,the data entry user interface can be automatically generated and/orupdated when the user defines the data set. The data entry userinterface can be compatible with different types of front end systems.In various embodiments, a data storage construct for storing data in adatastore of the data set input through the data entry user interface ofthe data collection construct is automatically defined based on the userinput. A data storage construct can be defined by automatically definingtable schema (and/or other schema) and index mappings for retrievingdata of the data set input through the data entry user interfaceaccording to the data collection construct and stored in the datastore.In some embodiments, the data storage construct does not define and/orotherwise enforce any schema (e.g., if the datastore lacks a schema oris a blob store). For example, the data entry user interface canvalidate the user input and provide feedback directly to the user.Further, the data storage construct can be defined based on the userinput while refraining from querying the user for additional input fordefining the data storage construct. In various embodiments, queries foruse in retrieving the data in the data set input through the data entryuser interface and stored in the datastore using the data storageconstruct are automatically defined. Queries for use in retrieving thedata in the data set input through the data entry user interface andstored in the datastore can be automatically defined as part of definingthe data storage construct. In certain embodiments, additional userinput indicating modifications to the data set can be received.Additional user input indicating modifications to the data set can bereceived through the data entry user interface included as part of thedefined data collection construct. In various embodiments, the datacollection construct, the data storage construct, and the queries areupdated based on the additional user input indicating modifications tothe data set.

FIG. 1 illustrates an example environment 100 for entering data. Theexample environment 100 includes a repository datastore 102. In someembodiments, the repository datastore 102 comprises a central repositorydatastore configured to store data in a centralized location. In someembodiments, the repository datastore 102 may comprise one or morenon-central repositories (e.g., distributed repositories) instead of, orin addition to, a central repository. The one or more non-centralrepositories may be configured to store data in one or morenon-centralized locations. This may allow, for example, differententities having different requirements for permissions to share thesystem for data entry/collection without sharing a data storageconstruct. Additionally, this may allow users to independently scale outthe data storage construct for high data availability without affectingother aspects of the system. It will be appreciated that reference to acentral repository. For example, the repository datastore 102 can storedata for an enterprise in a centralized location. Further, therepository datastore 102 can store data in a location remote from asource of the data. For example, the repository datastore 102 can beimplemented as a cloud-based datastore configured to store data remotefrom an enterprise system that generates the data.

As shown in FIG. 1, the example environment 100 also includes acustomizable data entry system 104. The example environment 100 caninclude one or more processors and memory. The one or more processorsand memory of the example environment 100 can be included as part of thecustomizable data entry system 104. The processors can be configured toperform various operations of the customizable data entry system 104 byinterpreting machine-readable instructions. The customizable data entrysystem 104 can be implemented through, at least in part, or otherwiseaccessed through a graphical user interface presented to a user. Invarious embodiments, the customizable data entry system 104 can beimplemented through, at least in part, a graphical user interfacepresented to a user as part of a data entry user interface.

In various embodiments, the customizable data entry system 104 isconfigured to store and retrieve data stored in the repository datastore102. The customizable data entry system 104 can store and retrieve datastored in the repository datastore 102 through one or an applicablecombination of a local area network, a wide area network, an enterprisenetwork, and a local device. In various embodiments, the customizabledata entry system 104 can store and retrieve data stored in therepository 102 that is entered through the customizable data entrysystem 104 by a user. More specifically, the customizable data entrysystem 104 can store and retrieve all or portions of data in a data setthat is input through the customizable data entry system 104 and storedin the repository 102 by the customizable data entry system 104. Invarious embodiments, the customizable data entry system 104 can send allor portions of a data set stored locally on a system or part of anetwork on which the customizable data entry system 104 is implementedto the repository 102, for use in storing all or portions of a data setat the repository 102.

In various embodiments, the customizable data entry system 104 canpresent or cause presentation of a data entry graphical user interface,hereinafter referred to as a data entry user interface, to a user foruse in inputting data by the user. The customizable data entry system104 can generate a data entry user interface based on input receivedfrom a user as part of a data collection construct. Additionally, thecustomizable data entry system 104 can modify an already created dataentry user interface based on input received from a user as part ofmodifying the data collection construct according to the user input. Insome embodiments, the customizable data entry system 104 canautomatically generate and/or update the data entry user interface(e.g., when the user defines a data set). The data entry user interfacecan be compatible with different types of front end systems.

As shown in FIG. 1, in some embodiments, the customizable data entrysystem 104 can include a data collection construct management engine106, a data storage construct management engine 108, a repositorystorage engine 112, and a datastore 110. The data collection constructmanagement engine 106, the data storage construct management engine 108,and the repository storage engine 112 can be executed by theprocessor(s) of the customizable data entry system 104 to performvarious operations including those described in reference to the datacollection construct management engine 106, the data storage constructmanagement engine 108, and the repository storage engine 112.

In various embodiments, the data collection construct management engine106 is configured to define a data collection construct for use incollecting data in a data set from a user. In defining, a datacollection construct for use in collecting data in a data set, the datacollection construct management engine 106 can generate and update adata collecting construct. For example, the data collection constructmanagement engine 106 can modify an already created data collectionconstruct. A data collection construct can include a type of data in adata set to collect, a format in which to collect data in a data set,needed fields for collecting data, rules associated with collecting thedata through a data collection construct, and a data entry userinterface for use in collecting data in a data set. For example, a datacollection construct created by the data collection construct managementengine 106 can include a data entry user interface with fields a usercan populate based on a data type defined for the fields. In anotherexample, the data collection construct management engine 106 can modifya data collection construct by adding a field to a form as part of adata entry user interface. In yet another example, a data collectionconstruct created by the data collection construct management engine 106can include validation constraints for validating data entered throughthe data collection construct.

In various embodiments, the data collection construct management engine106 is configured to define a data collection construct based on userinput. In defining a data collection construct based on user input, thedata collection construct management engine 106 can generate a new datacollection construct for use in collecting data based on the user input.For example, the data collection construct management engine 106 cangenerate a data entry user interface of a specific format for collectingdata of a specific type, as indicated by user input indicating theformat in which to collect the specific type of data. Further, indefining a data collection construct based on user input, the datacollection construct management engine 106 can modify an already createddata collection construct for use in collecting data based on the userinput. For example, the data collection construct management engine 106can change a format of a data entry user interface of an already createddata collection construct based on user input specifying a new format.

In various embodiments, the data collection construct management engine106 is configured to use a previously defined data collection constructto define a data collection construct. For example, the data collectionconstruct management engine 106 can use a form of a previously defineddata collection construct to define a new data collection construct. Inusing a previously defined data collection construct to define a datacollection construct, the data collection construct management engine106 can group, chain, or nest the defined data collection construct withthe previously defined data collection construct. For example, the datacollection construct management engine 106 can associate a datacollection construct used in collecting data for a specific organizationwith a previously defined data collection construct for theorganization. In another example, the data collection constructmanagement engine 106 can nest a data collection construct with apreviously defined data collection construct to cause data entered tothe data collection to also be entered in the previously defined datacollection construct after being entered through the data collectionconstruct.

In various embodiments, the data collection construct management engine106 is configured to analyze data at the data collection construct as itis entered through the data collection construct. In analyzing data atthe data collection construct as it is entered through the datacollection construct, the data collection construct management engine106 can validate the data at the data collection construct. For example,if validation constraints specify data entered into a field can onlyinclude numbers, then the data collection construct management engine106 can validate data entered into the field to ensure the entered datadoes not include letters.

In various embodiments, the data collection construct management engine106 is configured to present or cause presentation of a data entry userinterface to a user for purposes of providing functionalities to theuser for entering data through the interface. The data collectionconstruct management engine 106 can present a data entry user interfaceto a user as defined by a data collection construct. For example, if adefined data collection construct specifies to present a data entry userinterface including a graph node, then the data collection constructmanagement engine 106 can present a data entry user interface includingthe graph node to a user. In another example, if a data collectionconstruct is modified to change a user interface from including a graphnode to a table row, then the data collection construct managementengine 106 can modify a data entry user interface from presenting thegraph node to the table row.

In various embodiments, the data storage construct management engine 108is configured to define a data storage construct. A data storageconstruct created by the data storage construct management engine 108can include either or both table schema and index mappings for storingdata through the data storage construct. Additionally, a data storageconstruct created by the data storage construct management engine 108can include queries for use in retrieving data stored according to thedata storage construct. For example, a data storage construct created bythe data storage construct management engine 108 can include queries foruse in presenting to a user data entered into fields as the user entersthe data into the fields. The data storage construct management engine108 can define a data storage construct for use in storing data enteredthrough a data collection construct defined by the data collectionconstruct management engine. Additionally, the data storage constructmanagement engine 108 can define a data storage construct for use instoring data at the datastore 110.

In various embodiments, the datastore 110 can be implemented locallywith respect to the customizable data entry system 104. For example, thedatastore 110 can be implemented on a device used to present a dataentry user interface to a user in the operation of the customizable dataentry system 104. In another example, the datastore 110 can beimplemented within a local area network or an enterprise network of auser entering data through the customizable data system 104.

In various embodiments, the data storage construct management engine 108is configured to define a data storage construct specifically associatedwith a data collection construct. In being associated with a datacollection construct, a data storage construct can be used to store dataentered through the data collection construct. For example, the datastorage construct management engine 108 can define a new data storageconstruct associated with a data collection construct. In anotherexample, the data storage construct management engine 108 can associatean already created data storage construct with a data collectionconstruct when the data collection construct is created. A data storageconstruct defined by the data storage construct management engine 108can be associated with a plurality of data collection constructs. Forexample, a data storage construct defined by the data storage constructmanagement engine 108 can be associated with data collection constructswith data entry user interfaces configured to collect data of a specifictype. In some embodiments, a data collection construct can be associatedwith a plurality of data storage constructs. This may, for example, behelpful as different datastores are optimized for varying performancegain (e.g., search, availability, batch entry, and/or the like).

In various embodiments, the data storage construct management engine 108can automatically define a data storage construct for a data collectionconstruct. In automatically defining a data storage construct for a datacollection construct, the data storage construct management engine 108can automatically define the data storage construct for the datacollection construct absent user input specifying how to define the datastorage construct. Additionally, in automatically defining a datastorage construct for a data collection construct, the data storageconstruct management engine 108 can define a data storage constructabsent input from a developer. In defining a data storage construct fora data collection construct, the data storage construct managementengine 108 can automatically define a data storage construct based onreceived user input defining the data collection construct. For example,if a data collection construct is defined to collect a specific type ofdata based on user input, then the data storage construct managementengine 108 can define a data storage construct for the data collectionconstruct based on the specific type of data. In another example, if adata collection construct is defined to collect data using a specificformat of a data entry user interface, then the data storage constructmanagement engine 108 can define a data storage construct for storingdata input through the specific format of data entry.

In various embodiments, the data storage construct management engine 108is configured to automatically define a data storage construct based ondata storage construct definition rules. Data storage constructdefinition rules include applicable rules for defining a data storageconstruct without specific instructions from a user regarding defining adata storage construct. For example, data storage construct definitionrules can indicate one or a combination of table schema, index mappings,and queries to use in defining a data storage construct. Data storageconstruct definition rules can be specific to aspects of collectingdata. For example, data storage construction rules can be specific to adata type of data collected using a data collection construction. Inanother example, data storage construction rules can be specific to aform used in collecting data using a data collection construct.

In various embodiments, the data storage construct management engine 108is configured to analyze data entered through a defined data collectionconstruct and stored according to a defined data storage construct. Inanalyzing data entered through a defined data collection construct andstored according to a defined data storage construct, the data storageconstruct management engine 108 can either or both collect granularmetrics of the data and gather analytics of incremental data of thedata. For example, the data storage construct management engine 108 cananalyze data input through a data collection construct and storedaccording to a defined data storage construct to determine averagevalues of the data input into certain fields. In another example, thedata storage construct management engine 108 can analyze data inputthrough a data collection construct and stored according to a definedata storage construct to determine changes to the data over time.

In various embodiments, the data storage construct management engine 108is configured to validate data stored according to a data storageconstruct. More specifically, the data storage construct managementengine 108 can validate data stored in the datastore 110 according to adata storage construct. For example, the data storage constructmanagement engine 108 can determine whether data stored according to adata storage construct improperly includes null values. In validatingdata stored according to a data storage construct, the data storageconstruct management engine 108 can validate the data according to datavalidation constraints. For example, if data validation constraintsspecify that data cannot be greater than three symbols, then the datastorage construct management engine 108 can validate data to checkwhether data stored according to a data storage construct at thedatastore 110 is greater than three symbols.

In some embodiments, the data storage construct management engine 108 isconfigured to migrate (e.g., transform) data stored based on changes tothe data collection construct. Manual user intervention when it comes tomigration may be permissible (e.g., for safety and correctness).

In various embodiments, the repository storage engine 112 is configuredto control transfer of data to the centralized datastore 102. Therepository storage engine 112 can control transfer of data collectedaccording to a data collection construct to the centralized datastore102. Additionally, the repository storage engine 112 can controltransfer of data stored in a datastore according to a data storageconstruct to the centralized datastore 102. The repository storageengine 112 can control transfer of data collected according to a datacollection construct defined by the data collection construct managementengine 106. Further, the repository storage engine 112 can controltransfer of data stored in the datastore 110 according to a data storageconstruct defined by the data storage construct management engine 108.In controlling transfer of data, the repository storage engine 112 canselect specific data to transfer and subsequently transfer that data tothe repository 102.

In various embodiments, the repository storage engine 112 is configuredto transfer data to the repository 102 according to either or both adata collection construct and a data storage construct. Morespecifically, the repository storage engine 112 can transfer data to therepository 102 based on one or a combination of a data type of dataentered, a time at which data is entered, and a user who entered data.For example, the repository storage engine 112 can extract only datathat has been updated in the last day, and subsequently transfer thedata from the datastore 110 to the repository 102. In another example,the repository storage engine 112 can extract data of a specific typethat has been entered, and subsequently transfer the data from thedatastore 110 to the repository 102.

FIG. 2 illustrates an example environment 200 for defining a datacollection construct. As shown in FIG. 2, the example environment 200includes a data collection construct management engine 202. The exampleenvironment 200 can include one or more processors and memory. The oneor more processors and memory of the example environment 200 can beincluded as part of the data collection construct management engine 202.The processors can be configured to perform various operations of thedata collection construct management engine 202 by interpretingmachine-readable instructions. The data collection construct managementengine 202 can be implemented through, at least in part, or otherwiseaccessed through a graphical user interface presented to a user.

In various embodiments, the data collection construct management engine202 is configured to receive user input for use in defining a datacollection construct. The data collection construct management engine202 can receive user input to define a new data collection construct.For example, the data collection construct management engine 202 canreceive user input defining a form of a data entry user interface to usein collecting data through a data collection construct. Additionally,the data collection construct management engine 202 can receive userinput to modify an already existing data collection construct. Forexample, the data collection construct management engine 202 can receiveuser input indicating an added field to a data entry user interface touse in collecting data through a data collection construct.

As shown in FIG. 2, in some embodiments, the data collection constructmanagement engine 202 can include a user input communication engine 204,a user input datastore 206, a data collection construct definitionengine 208, a data collection construct datastore 210, a data entry userinterface presentation engine 212, and a data collection construct dataanalytics engine 214. The user input communication engine 204, the datacollection construct definition engine 208, the data entry userinterface presentation engine 212, and the data collection constructdata analytics engine 214 can be executed by the processor(s) of thedata collection construct management engine 202 to perform variousoperations including those described in reference to the user inputcommunication engine 204, the data collection construct definitionengine 208, the data entry user interface presentation engine 212, andthe data collection construct data analytics engine 214.

In various embodiments, the user input communication engine 204 isconfigured to receive user input regarding data entry. The user inputcommunication engine 204 can receive user input regarding a datacollection construct. For example, the user input communication engine204 can receive user input indicating a form in which to collect datathrough a data entry user interface. The user input communication engine204 can receive user input indicating changes to make to an alreadydefined data collection construct. For example, the user inputcommunication engine 204 can receive user input indicating to remove afield from a data entry user interface as part of a data collectionconstruct. The user input communication engine 204 can store receiveduser input related to a data collection construct in the user inputdatastore 206.

In various embodiments, the data collection construct definition engine208 is configured to define a data collection construct for use incollecting data. The data collection definition engine 208 can define adata collection construct based on user input stored in the user inputdatastore 206 and received by the user input communication engine 204.For example, if user input indicates a data entry user interface shouldbe in a table format, then the data collection construct definitionengine 208 can define a data collection construct to include a dataentry user interface including a table. The data collection constructdefinition engine 208 can define a data collection construct to indicatea type of data in a data set to collect, a format in which to collectdata in a data set, needed fields for collecting data, rules associatedwith collecting the data through a data collection construct, and a dataentry user interface for use in collecting data in a data set.

In various embodiments, the data collection construct definition engine208 is configured to define a data collection construct using an alreadyexisting data collection construct. More specifically, the datacollection construct definition engine 208 can use computer executableinstructions defining an already existing data collection construct todefine a new data collection construct. For example, the data collectionconstruct definition engine 208 can create a data collection constructusing computer executable instructions for a data entry user interfacein a previously defined data collection construct. The data collectionconstruct definition engine 208 can use a previously created datacollection construct to define a new data collection construct based onone or a combination of a data type, an enterprise associated with auser, and a specific user. For example, the data collection constructdefinition engine 208 can create a data collection construct for a userassociated with an enterprise using a previously defined data collectionconstruct for the enterprise.

In various embodiments, the data collection construct definition engine208 is configured to modify an already existing data construct. The datacollection construct definition engine 208 can modify an alreadyexisting data construct based on user input stored in the user inputdatastore 206 and received by the user input communication engine 204.For example, if user input indicates to change a form of a datacollection construct from a graph node format to a table row format,then the data collection construct definition engine 208 can modify thedata collection construct to include a data entry user interface in thetable row format. The graph node format may indicate relationshipsbetween entries in a data collection construct. Accordingly, entries ofa data storage construct do not necessarily have to stem from the samedata set. In another example, if user input indicates adding a field toa data collection construct, then the data collection constructdefinition engine 208 can change the data collection construct toinclude the field.

In various embodiments, the data collection construct definition engine208 is configured to generate and update data collection construct datastored in the data collection construct datastore 210 to indicate adefined data collection construct. For example, the data collectionconstruct definition engine 208 can generate data collection constructdata stored in the data collection construct datastore 210 to indicate anewly defined data collection construct. In another example, the datacollection construct definition engine 208 can modify data collectionconstruct data stored in the data collection construct datastore 210 toindicate changes made to a data collection construct.

In various embodiments, the data collection construct definition engine208 can group, chain, or nest the defined data collection construct withthe previously defined data collection construct. For example, the datacollection construct definition engine 208 can associate a datacollection construct used in collecting data for a specific company witha previously defined data collection construct for the company. Inanother example, the data collection construct definition engine 208 cannest a data collection construct defined for a user into a previouslydefined data collection construct defined for the user.

In various embodiments, the data entry user interface presentationengine 212 is configured to present a data entry user interface of adefined data collection construct to a user for purposes of receivingdata entered through the user interface by a user. The data entry userinterface presentation engine 212 can use data collection construct dataof a defined data collection construct stored in the data collectionconstruct datastore 210 to present a data entry user interface to auser. For example, if data collection construct data of a defined datacollection construct indicates presenting a user interface in a graphnode form, then the data entry user interface presentation engine 212can present an interface in graph node form to a user. The data entryuser interface presentation engine 212 can modify a data entry userinterface to a user based on modifications made to a data collectionconstruct. For example, if a data collection construct is modified toremove a field, then the data entry user interface presentation engine212 can modify a data entry user interface presented to a user byremoving the field from the interface.

In various embodiments, the data collection construct data analyticsengine 214 is configured to perform analytics on data entered through adata collection construct. The data collection construct data analyticsengine 214 can perform analytics on data as it is entered through a datacollection construct. More specifically, the data collection constructdata analytics engine 214 can validate data as it is entered through adata collection construct according to validation constraints. Forexample, if validation constraints indicate data must be at least threecharacters long and a user enters data that is only two characters long,then the data collection construct data analytics engine 214 can providea notification to a user, through a data entry user interface,indicating that the user has entered invalid data.

In some embodiments, the data collection construct data analytics engine214 is configured to cooperate with one or more services (e.g., an eventservice). This may allow, for example, services to listen for changes inthe datastore and behave/react accordingly. For example, if a new entryis added to a user defined dataset, another service can listen for newentries to the data set and perform search and/or aggregations on behalfof the user.

FIG. 3 illustrates an example environment 300 for defining a datastorage construct. As shown in FIG. 3, the example environment 300includes a data storage construct management engine 302. The exampleenvironment 300 can include one or more processors and memory. The oneor more processors and memory of the example environment 300 can beincluded as part of the data storage construct management engine 302.The processors can be configured to perform various operations of thedata storage construct management engine 302 by interpretingmachine-readable instructions. The data storage construct managementengine 302 can be implemented through, at least in part, or otherwiseaccessed through a graphical user interface presented to a user.

In various embodiments, the data storage construct management engine 302is configured to define a data storage construct for use in storing dataentered through a data collection construct. The data storage constructmanagement engine 302 can automatically define a data storage constructbased on a data collection construct defined according to user input.For example, in defining a data storage construct, the data storageconstruct management engine 302 can define table schema and indexmappings based on a defined data collection construct. In anotherexample, in defining a data storage construct, the data storageconstruct management engine 302 can define queries for use in retrieveddata stored according to the data storage construct based on a defineddata collection construct.

As shown in FIG. 3, in some embodiments, the data storage constructmanagement engine 302 can include a data collection construct datastore304, a data storage construct definition engine 306, a data storageconstruct datastore 308, a data storage engine 310, a datastore 312, anda data storage construct data analytics engine 314. The data storageconstruct definition engine 306, the data storage engine 310, and thedata storage construct data analytics engine 314 can be executed by theprocessor(s) of the data storage construct management engine 302 toperform various operations including those described in reference to thedata storage construct definition engine 306, the data storage engine310, and the data storage construct data analytics engine 314.

In various embodiments, the data collection construct datastore 304 isconfigured to store data collection construct data indicating a defineddata collection construct. A data collection construct indicated by datacollection construct data stored in the data collection constructdatastore 304 can be maintained by an applicable engine for defining adata collection construct, such as the data collection constructmanagement engines described in this paper. Data collection constructdata stored in the data collection construct datastore 304 can include atype of data in a data set to collect, a format in which to collect datain a data set, needed fields for collecting data, rules associated withcollecting the data through a data collection construct, and a dataentry user interface for use in collecting data in a data set. Datacollection construct data stored in the data collection constructdatastore 304 can be modified based on user input. For example, datacollection construct data stored in the data collection constructdatastore 304 can be updated to indicate changes made to a defined datacollection construct based on user input.

In various embodiments, the data storage construct definition engine 306is configured to define a data storage construct for use in storing dataentered through a data collection construct. The data storage constructdefinition engine 306 can define a data storage construct automaticallyfor a data collection construct based on the data collection construct.More specifically, the data storage construct definition engine 306 canautomatically define a data storage construct for a data collectionconstruct absent user input indicating how to define the data storageconstruct. For example, the data storage construct definition engine 306can define a data storage construct based on a data type a datacollection construct is defined to collect. The data storage constructdefinition engine 306 can generate and update data storage constructdata stored in the data storage construct datastore 308 to indicate adefined data storage construct.

In various embodiments, the data storage construct definition engine 306can define either or both table schema and index mappings in defining adata storage construct. Additionally, the data storage constructdefinition engine 306 can define queries, as included as part of a datastorage construct, for use in retrieving data stored according to thedata storage construct. For example, the data storage constructdefinition engine 306 can define queries for use in retrieving specificportions of data stored according to a data storage construct.

In various embodiments, the data storage construct definition engine 306is configured to define a data storage construct according to datastorage construct definition rules. Data storage construct definitionrules can be specific to one or a combination of a data type collectedaccording to a data collection construct, a user who created a datacollection construct, a user who is utilizing a data collectionconstruct to enter data, and an entity or enterprise associated with adata collection construct. For example, data storage constructdefinition rules can be unique to a company with employees using a datacollection construct to enter data.

In various embodiments, the data storage construct definition engine 306is configured to define a data storage construct based on alreadycreated data storage constructs. For example, the data storage constructdefinition engine 306 can use an already created data storage constructfor storing a specific type of data to create a new data storageconstruct for storing the specific type of data. In another example, thedata storage construct definition engine 306 can use an already createddata storage construct created for a user to define a new data storageconstruct for the user. In some embodiments, other users may alsoleverage existing data storage constructs regardless of who the originalowner/creator was (e.g., depending on permissions).

In various embodiments, the data storage engine 310 is configured tostore data in the datastore 312 according to a data storage constructindicated by data storage construct data stored in the data storageconstruct datastore 308. For example, the data storage engine 310 canstore data in the datastore 312 according to index mappings defined aspart of a data storage construct. The data storage engine 310 can storedata entered through a data collection construct associated with a datastorage construct. For example, if a data storage construct is definedfor a data collection construct, then the data storage engine 310 canstore data entered through the data collection construct using the datastorage construct.

In various embodiments, the data storage engine 310 is configured toretrieve data from the datastore 312. The data storage engine 310 canretrieve data from the datastore 312 using a data storage construct usedto store the data in the datastore 312. For example, the data storageengine 310 can use queries included as part of a data storage constructto retrieve and/or otherwise obtain data stored in the datastore 312using the data storage construct. For example, the data storage engine310 can fetch specific records, find records that a user did not knowexisted, and/or finding related records to keywords (e.g., keywordsmanually entered by a user). As used herein, a record is equivalent to adata entity that is entered in a data collection construct.

In various embodiments, the data storage engine 310 is configured tomodify a data storage construct based on modifications made to a datacollection construct associated with the data storage construct. Inmodifying a data storage construct based on modifications made to a datacollection construct, the data storage engine 310 can modify one or acombination of a table schema, index mappings, and queries of the datastorage construct. For example, if a user modifies a data collectionconstruct to include an additionally data entry field, then the datastorage engine 310 can modify an index mapping of a data storageconstruct to allow for storage data entered through the additional dataentry field.

In various embodiments, the data storage construct data analytics engine314 is configured to perform analytics of data stored in the datastore312 according to a data storage construct. The data storage constructdata analytics engine 314 can either or both collect granular metrics ofthe data and gather analytics of incremental data of the data. Forexample, the data storage construct data analytics engine 314 candetermine a number of null values in a data set. Further, the datastorage construct data analytics engine 314 can analyze the data at astorage construct level by analyzing the data as it is stored in thelocal datastore 312 according to the data storage construct. Morespecifically, the data storage construct data analytics engine 314 cananalyze data stored in datastore 312 before it is transferred to arepository, e.g. a remote system.

In various embodiments, the data storage construct data analytics engine314 is configured to validate data stored in the datastore 312. The datastorage construct data analytics engine 314 can validate data at a datastorage construct level, e.g. as it is stored in the datastore 312 andbefore it is transferred to a repository. In some embodiments,validation may also occur before the data enters the datastore using theuser interface that the client uses to enter data. Custom validationschemes (or, user-defined validation schemes) may be implemented. Customvalidation schemes may define, for example, when and/or how validationoccurs. The data storage construct data analytics engine 314 canvalidate data stored in the datastore 312 according to validationconstraints. For example, if validation constraints specify a fieldcannot have a null value, then the data storage construct data analyticsengine 314 can validate data to ensure the field does not have a nullvalue. The data storage construct data analytics engine 314 can providea notification to a user, through a data entry user interface,indicating entered data is invalid if the data storage construct dataanalytics engine 314 determines the entered data is invalid.

FIG. 4 illustrates an example environment 400 for selectivelytransferring data to a repository. As shown in FIG. 4, the exampleenvironment 400 includes a repository 402. The repository 402 can beimplemented at a remote location. For example, the repository 402 can beimplemented in the cloud. Additionally, the repository 402 can bespecific to one or a plurality of entities or enterprises. For example,the repository 402 can be a remote data storage system of a company.

As shown in FIG. 4, the example environment 400 includes a repositorystorage engine 402. The example environment 400 can include one or moreprocessors and memory. The one or more processors and memory of theexample environment 400 can be included as part of the repositorystorage engine 402. The processors can be configured to perform variousoperations of the repository storage engine 402 by interpretingmachine-readable instructions.

In various embodiments, the repository storage engine 404 is configuredto selectively transfer stored data to the repository 402. Therepository storage engine 404 can selectively transfer data enteredthrough a data collection construct defined based on user input.Additionally, the repository storage engine 404 can selectively transferdata stored according to a data storage construct automatically createdbased on a data collection construct.

As shown in FIG. 4, in some embodiments, the repository storage engine404 can include a datastore 406, a data selection engine 408, and arepository data transfer engine 410. The data selection engine 408 andthe repository data transfer engine 410 can be executed by theprocessor(s) of the repository storage engine 404 to perform variousoperations including those described in reference to the data selectionengine 408 and the repository data transfer engine 410.

In various embodiments, the datastore 406 is configured to store data ofa data set capable of being transferred to the repository 402. Datastored in the datastore 406 can be entered through a data collectionconstruct defined based on user input. Additionally, data stored in thedatastore 406 can be stored according to a data storage constructautomatically defined based on a data collection construct.

In various embodiments, the data selection engine 408 is configured toselect data stored in the datastore 406 to transfer to the repository402. The data selection engine 408 can select data to transfer to therepository 402 based on one or a combination of a data type of the data,a user who entered the data, and a time when the data was entered ormodified. For example, the data selection engine 408 can select data totransfer to the repository 402 once the data is created or updated. Thedata selection engine 408 can select data to transfer to the repositorybased on data size. More specifically, the data selection engine 408 canselect up to a specific amount of data to transfer to the repository402. For example, the data selection engine 408 can select 100 Gb ofdata stored in the datastore 406 to transfer to the repository 402. Therate of transfer can be a function of resource constraints and/or clientrequirements. For example, if the environment 400 is under stress, theamount of data transferred back to the repository 402 at any given timecan be low (e.g., in order to not add stress to the other system(s) inthe environment 400). If the client requirements are to have strongconsistency guarantees between the data in the engine 404 and therepository 402, then the transfer of data may be continuous and theresource demands of the engine 404 may be greater.

In various embodiments, the data selection engine 408 is configured toperform auditing functionality. The auditing functionality may betoggled on/off. The auditing functionality can provide a fine grain listof every instance that data has been inserted, updated and/or deletedcan be chronicled. The resulting audit log can also be sent to therepository 402 for storage.

In various embodiments, the repository data transfer engine 410 isconfigured to transfer data stored in the datastore 406 to therepository. The repository data transfer engine 410 can transfer dataselected by the data selection engine 408. For example, the repositorydata transfer engine 410 can transfer a subset of data selected by thedata selection engine 408 based on the subset of the data being updatedby a user. The repository data transfer engine 410 can transfer data tothe repository 402 at scheduled times. For example, the repository datatransfer engine 410 can transfer data to the repository 402 every day atthe same time.

FIG. 5 illustrates a flowchart of an example method 500, according tovarious embodiments of the present disclosure. The method 500 may beimplemented in various environments including, for example, theenvironment 100 of FIG. 1. The operations of method 500 presented beloware intended to be illustrative. Depending on the implementation, theexample method 500 may include additional, fewer, or alternative stepsperformed in various orders or in parallel. The example method 500 maybe implemented in various computing systems or devices including one ormore processors.

At block 502, user input defining a data set is received. An applicableengine for receiving user input, such as the user input communicationengines described in this paper, can receive user input defining a dataset. User input received at block 502 can include applicable informationdescribing a desired way in which to collect data. For example, userinput received at block 502 can indicate fields a data entry userinterface should have for gathering data in the data set.

At block 504, a data collection construct for entering data is definedbased on the user input. An applicable engine for defining a datacollection construct, such as the data collection construct definitionengines described in this paper, can define a data collection constructfor entering data based on the user input. A defined data collectionconstruct can include a defined data entry user interface for use by theuser in inputting data in the data set.

At block 506, a data storage construct for the data collection constructis defined based on the user input used to define the data collectionconstruct. An applicable engine for defining a data storage construct,such as the data storage construct definition engines described in thispaper, can automatically define a data storage construct for the datacollection construct based on the user input. A data storage constructcan be automatically defined based on the data collection constructwithout receiving explicit input defining the data storage constructfrom the user. Additionally, a data storage construct can beautomatically defined using previously defined data storage constructs.

At block 508, queries for use in retrieving the data in the data setentered through the data collection construct and stored using the datastorage construct are automatically defined. An applicable engine fordefining a data storage construct, such as the data storage constructdefinition engines described in this paper, can define queries for usein retrieving the data in the data set entered through the datacollection construct and stored using the data storage construct.Queries for retrieving the data in the data set can be included as partof the defined data storage construct.

At block 510, the data collection construct, the data storage construct,and the queries are automatically updated based on received additionaluser input indicating modifications to the data set. An applicableengine for defining a data collection construct, such as the datacollection construct definition engines described in this paper, canautomatically update the data collection construct based on receivedadditional user input indicating modifications to the data set. Anapplicable engine for defining a data storage construct, such as thedata storage construct definition engines described in this paper, canautomatically update the data storage construct and the queries based onreceived additional user input indicating modifications to the data set.

Hardware Implementation

The techniques described herein are implemented by one or morespecial-purpose computing devices. The special-purpose computing devicesmay be hard-wired to perform the techniques, or may include circuitry ordigital electronic devices such as one or more application-specificintegrated circuits (ASICs) or field programmable gate arrays (FPGAs)that are persistently programmed to perform the techniques, or mayinclude one or more hardware processors programmed to perform thetechniques pursuant to program instructions in firmware, memory, otherstorage, or a combination. Such special-purpose computing devices mayalso combine custom hard-wired logic, ASICs, or FPGAs with customprogramming to accomplish the techniques. The special-purpose computingdevices may be desktop computer systems, server computer systems,portable computer systems, handheld devices, networking devices or anyother device or combination of devices that incorporate hard-wiredand/or program logic to implement the techniques.

Computing device(s) are generally controlled and coordinated byoperating system software, such as iOS, Android, Chrome OS, Windows XP,Windows Vista, Windows 7, Windows 8, Windows Server, Windows CE, Unix,Linux, SunOS, Solaris, iOS, Blackberry OS, VxWorks, or other compatibleoperating systems. In other embodiments, the computing device may becontrolled by a proprietary operating system. Conventional operatingsystems control and schedule computer processes for execution, performmemory management, provide file system, networking, I/O services, andprovide a user interface functionality, such as a graphical userinterface (“GUI”), among other things.

FIG. 6 is a block diagram that illustrates a computer system 600 uponwhich any of the embodiments described herein may be implemented. Thecomputer system 600 includes a bus 602 or other communication mechanismfor communicating information, one or more hardware processors 604coupled with bus 602 for processing information. Hardware processor(s)604 may be, for example, one or more general purpose microprocessors.

The computer system 600 also includes a main memory 606, such as arandom access memory (RAM), cache and/or other dynamic storage devices,coupled to bus 602 for storing information and instructions to beexecuted by processor 604. Main memory 606 also may be used for storingtemporary variables or other intermediate information during executionof instructions to be executed by processor 604. Such instructions, whenstored in storage media accessible to processor 604, render computersystem 600 into a special-purpose machine that is customized to performthe operations specified in the instructions.

The computer system 600 further includes a read only memory (ROM) 608 orother static storage device coupled to bus 602 for storing staticinformation and instructions for processor 604. A storage device 610,such as a magnetic disk, optical disk, or USB thumb drive (Flash drive),etc., is provided and coupled to bus 602 for storing information andinstructions.

The computer system 600 may be coupled via bus 602 to a display 612,such as a cathode ray tube (CRT) or LCD display (or touch screen), fordisplaying information to a computer user. An input device 614,including alphanumeric and other keys, is coupled to bus 602 forcommunicating information and command selections to processor 604.Another type of user input device is cursor control 616, such as amouse, a trackball, or cursor direction keys for communicating directioninformation and command selections to processor 604 and for controllingcursor movement on display 612. This input device typically has twodegrees of freedom in two axes, a first axis (e.g., x) and a second axis(e.g., y), that allows the device to specify positions in a plane. Insome embodiments, the same direction information and command selectionsas cursor control may be implemented via receiving touches on a touchscreen without a cursor.

The computing system 600 may include a user interface module toimplement a GUI that may be stored in a mass storage device asexecutable software codes that are executed by the computing device(s).This and other modules may include, by way of example, components, suchas software components, object-oriented software components, classcomponents and task components, processes, functions, attributes,procedures, subroutines, segments of program code, drivers, firmware,microcode, circuitry, data, databases, data structures, tables, arrays,and variables.

In general, the word “module,” as used herein, refers to logic embodiedin hardware or firmware, or to a collection of software instructions,possibly having entry and exit points, written in a programminglanguage, such as, for example, Java, C or C++. A software module may becompiled and linked into an executable program, installed in a dynamiclink library, or may be written in an interpreted programming languagesuch as, for example, BASIC, Perl, or Python. It will be appreciatedthat software modules may be callable from other modules or fromthemselves, and/or may be invoked in response to detected events orinterrupts. Software modules configured for execution on computingdevices may be provided on a computer readable medium, such as a compactdisc, digital video disc, flash drive, magnetic disc, or any othertangible medium, or as a digital download (and may be originally storedin a compressed or installable format that requires installation,decompression or decryption prior to execution). Such software code maybe stored, partially or fully, on a memory device of the executingcomputing device, for execution by the computing device. Softwareinstructions may be embedded in firmware, such as an EPROM. It will befurther appreciated that hardware modules may be comprised of connectedlogic units, such as gates and flip-flops, and/or may be comprised ofprogrammable units, such as programmable gate arrays or processors. Themodules or computing device functionality described herein arepreferably implemented as software modules, but may be represented inhardware or firmware. Generally, the modules described herein refer tological modules that may be combined with other modules or divided intosub-modules despite their physical organization or storage.

The computer system 600 may implement the techniques described hereinusing customized hard-wired logic, one or more ASICs or FPGAs, firmwareand/or program logic which in combination with the computer systemcauses or programs computer system 600 to be a special-purpose machine.According to one embodiment, the techniques herein are performed bycomputer system 600 in response to processor(s) 604 executing one ormore sequences of one or more instructions contained in main memory 606.Such instructions may be read into main memory 606 from another storagemedium, such as storage device 610. Execution of the sequences ofinstructions contained in main memory 606 causes processor(s) 604 toperform the process steps described herein. In alternative embodiments,hard-wired circuitry may be used in place of or in combination withsoftware instructions.

The term “non-transitory media,” and similar terms, as used hereinrefers to any media that store data and/or instructions that cause amachine to operate in a specific fashion. Such non-transitory media maycomprise non-volatile media and/or volatile media. Non-volatile mediaincludes, for example, optical or magnetic disks, such as storage device610. Volatile media includes dynamic memory, such as main memory 606.Common forms of non-transitory media include, for example, a floppydisk, a flexible disk, hard disk, solid state drive, magnetic tape, orany other magnetic data storage medium, a CD-ROM, any other optical datastorage medium, any physical medium with patterns of holes, a RAM, aPROM, and EPROM, a FLASH-EPROM, NVRAM, any other memory chip orcartridge, and networked versions of the same.

Non-transitory media is distinct from but may be used in conjunctionwith transmission media. Transmission media participates in transferringinformation between non-transitory media. For example, transmissionmedia includes coaxial cables, copper wire and fiber optics, includingthe wires that comprise bus 602. Transmission media can also take theform of acoustic or light waves, such as those generated duringradio-wave and infra-red data communications.

Various forms of media may be involved in carrying one or more sequencesof one or more instructions to processor 604 for execution. For example,the instructions may initially be carried on a magnetic disk or solidstate drive of a remote computer. The remote computer can load theinstructions into its dynamic memory and send the instructions over atelephone line using a modem. A modem local to computer system 600 canreceive the data on the telephone line and use an infra-red transmitterto convert the data to an infra-red signal. An infra-red detector canreceive the data carried in the infra-red signal and appropriatecircuitry can place the data on bus 602. Bus 602 carries the data tomain memory 606, from which processor 604 retrieves and executes theinstructions. The instructions received by main memory 606 may retrievesand executes the instructions. The instructions received by main memory606 may optionally be stored on storage device 610 either before orafter execution by processor 604.

The computer system 600 also includes a communication interface 618coupled to bus 602. Communication interface 618 provides a two-way datacommunication coupling to one or more network links that are connectedto one or more local networks. For example, communication interface 618may be an integrated services digital network (ISDN) card, cable modem,satellite modem, or a modem to provide a data communication connectionto a corresponding type of telephone line. As another example,communication interface 618 may be a local area network (LAN) card toprovide a data communication connection to a compatible LAN (or WANcomponent to communicated with a WAN). Wireless links may also beimplemented. In any such implementation, communication interface 618sends and receives electrical, electromagnetic or optical signals thatcarry digital data streams representing various types of information.

A network link typically provides data communication through one or morenetworks to other data devices. For example, a network link may providea connection through local network to a host computer or to dataequipment operated by an Internet Service Provider (ISP). The ISP inturn provides data communication services through the world wide packetdata communication network now commonly referred to as the “Internet”.Local network and Internet both use electrical, electromagnetic oroptical signals that carry digital data streams. The signals through thevarious networks and the signals on network link and throughcommunication interface 618, which carry the digital data to and fromcomputer system 600, are example forms of transmission media.

The computer system 600 can send messages and receive data, includingprogram code, through the network(s), network link and communicationinterface 618. In the Internet example, a server might transmit arequested code for an application program through the Internet, the ISP,the local network and the communication interface 618.

The received code may be executed by processor 604 as it is received,and/or stored in storage device 610, or other non-volatile storage forlater execution.

Each of the processes, methods, and algorithms described in thepreceding sections may be embodied in, and fully or partially automatedby, code modules executed by one or more computer systems or computerprocessors comprising computer hardware. The processes and algorithmsmay be implemented partially or wholly in application-specificcircuitry.

The various features and processes described above may be usedindependently of one another, or may be combined in various ways. Allpossible combinations and sub-combinations are intended to fall withinthe scope of this disclosure. In addition, certain method or processblocks may be omitted in some implementations. The methods and processesdescribed herein are also not limited to any particular sequence, andthe blocks or states relating thereto can be performed in othersequences that are appropriate. For example, described blocks or statesmay be performed in an order other than that specifically disclosed, ormultiple blocks or states may be combined in a single block or state.The example blocks or states may be performed in serial, in parallel, orin some other manner. Blocks or states may be added to or removed fromthe disclosed example embodiments. The example systems and componentsdescribed herein may be configured differently than described. Forexample, elements may be added to, removed from, or rearranged comparedto the disclosed example embodiments.

Conditional language, such as, among others, “can,” “could,” “might,” or“may,” unless specifically stated otherwise, or otherwise understoodwithin the context as used, is generally intended to convey that certainembodiments include, while other embodiments do not include, certainfeatures, elements and/or steps. Thus, such conditional language is notgenerally intended to imply that features, elements and/or steps are inany way required for one or more embodiments or that one or moreembodiments necessarily include logic for deciding, with or without userinput or prompting, whether these features, elements and/or steps areincluded or are to be performed in any particular embodiment.

Any process descriptions, elements, or blocks in the flow diagramsdescribed herein and/or depicted in the attached figures should beunderstood as potentially representing modules, segments, or portions ofcode which include one or more executable instructions for implementingspecific logical functions or steps in the process. Alternateimplementations are included within the scope of the embodimentsdescribed herein in which elements or functions may be deleted, executedout of order from that shown or discussed, including substantiallyconcurrently or in reverse order, depending on the functionalityinvolved, as would be understood by those skilled in the art.

It should be emphasized that many variations and modifications may bemade to the above-described embodiments, the elements of which are to beunderstood as being among other acceptable examples. All suchmodifications and variations are intended to be included herein withinthe scope of this disclosure. The foregoing description details certainembodiments of the invention. It will be appreciated, however, that nomatter how detailed the foregoing appears in text, the invention can bepracticed in many ways. As is also stated above, it should be noted thatthe use of particular terminology when describing certain features oraspects of the invention should not be taken to imply that theterminology is being re-defined herein to be restricted to including anyspecific characteristics of the features or aspects of the inventionwith which that terminology is associated. The scope of the inventionshould therefore be construed in accordance with the appended claims andany equivalents thereof.

Engines, Components, and Logic

Certain embodiments are described herein as including logic or a numberof components, engines, or mechanisms. Engines may constitute eithersoftware engines (e.g., code embodied on a machine-readable medium) orhardware engines. A “hardware engine” is a tangible unit capable ofperforming certain operations and may be configured or arranged in acertain physical manner. In various example embodiments, one or morecomputer systems (e.g., a standalone computer system, a client computersystem, or a server computer system) or one or more hardware engines ofa computer system (e.g., a processor or a group of processors) may beconfigured by software (e.g., an application or application portion) asa hardware engine that operates to perform certain operations asdescribed herein.

In some embodiments, a hardware engine may be implemented mechanically,electronically, or any suitable combination thereof. For example, ahardware engine may include dedicated circuitry or logic that ispermanently configured to perform certain operations. For example, ahardware engine may be a special-purpose processor, such as aField-Programmable Gate Array (FPGA) or an Application SpecificIntegrated Circuit (ASIC). A hardware engine may also includeprogrammable logic or circuitry that is temporarily configured bysoftware to perform certain operations. For example, a hardware enginemay include software executed by a general-purpose processor or otherprogrammable processor. Once configured by such software, hardwareengines become specific machines (or specific components of a machine)uniquely tailored to perform the configured functions and are no longergeneral-purpose processors. It will be appreciated that the decision toimplement a hardware engine mechanically, in dedicated and permanentlyconfigured circuitry, or in temporarily configured circuitry (e.g.,configured by software) may be driven by cost and time considerations.

Accordingly, the phrase “hardware engine” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. As used herein,“hardware-implemented engine” refers to a hardware engine. Consideringembodiments in which hardware engines are temporarily configured (e.g.,programmed), each of the hardware engines need not be configured orinstantiated at any one instance in time. For example, where a hardwareengine comprises a general-purpose processor configured by software tobecome a special-purpose processor, the general-purpose processor may beconfigured as respectively different special-purpose processors (e.g.,comprising different hardware engines) at different times. Softwareaccordingly configures a particular processor or processors, forexample, to constitute a particular hardware engine at one instance oftime and to constitute a different hardware engine at a differentinstance of time.

Hardware engines can provide information to, and receive informationfrom, other hardware engines. Accordingly, the described hardwareengines may be regarded as being communicatively coupled. Where multiplehardware engines exist contemporaneously, communications may be achievedthrough signal transmission (e.g., over appropriate circuits and buses)between or among two or more of the hardware engines. In embodiments inwhich multiple hardware engines are configured or instantiated atdifferent times, communications between such hardware engines may beachieved, for example, through the storage and retrieval of informationin memory structures to which the multiple hardware engines have access.For example, one hardware engine may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware engine may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware engines may also initiate communications with input oroutput devices, and can operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented enginesthat operate to perform one or more operations or functions describedherein. As used herein, “processor-implemented engine” refers to ahardware engine implemented using one or more processors.

Similarly, the methods described herein may be at least partiallyprocessor-implemented, with a particular processor or processors beingan example of hardware. For example, at least some of the operations ofa method may be performed by one or more processors orprocessor-implemented engines. Moreover, the one or more processors mayalso operate to support performance of the relevant operations in a“cloud computing” environment or as a “software as a service” (SaaS).For example, at least some of the operations may be performed by a groupof computers (as examples of machines including processors), with theseoperations being accessible via a network (e.g., the Internet) and viaone or more appropriate interfaces (e.g., an Application ProgramInterface (API)).

The performance of certain of the operations may be distributed amongthe processors, not only residing within a single machine, but deployedacross a number of machines. In some example embodiments, the processorsor processor-implemented engines may be located in a single geographiclocation (e.g., within a home environment, an office environment, or aserver farm). In other example embodiments, the processors orprocessor-implemented engines may be distributed across a number ofgeographic locations.

Language

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Although an overview of the subject matter has been described withreference to specific example embodiments, various modifications andchanges may be made to these embodiments without departing from thebroader scope of embodiments of the present disclosure. Such embodimentsof the subject matter may be referred to herein, individually orcollectively, by the term “invention” merely for convenience and withoutintending to voluntarily limit the scope of this application to anysingle disclosure or concept if more than one is, in fact, disclosed.

The embodiments illustrated herein are described in sufficient detail toenable those skilled in the art to practice the teachings disclosed.Other embodiments may be used and derived therefrom, such thatstructural and logical substitutions and changes may be made withoutdeparting from the scope of this disclosure. The Detailed Description,therefore, is not to be taken in a limiting sense, and the scope ofvarious embodiments is defined only by the appended claims, along withthe full range of equivalents to which such claims are entitled.

It will be appreciated that an “engine,” “system,” “data store,” and/or“database” may comprise software, hardware, firmware, and/or circuitry.In one example, one or more software programs comprising instructionscapable of being executable by a processor may perform one or more ofthe functions of the engines, data stores, databases, or systemsdescribed herein. In another example, circuitry may perform the same orsimilar functions. Alternative embodiments may comprise more, less, orfunctionally equivalent engines, systems, data stores, or databases, andstill be within the scope of present embodiments. For example, thefunctionality of the various systems, engines, data stores, and/ordatabases may be combined or divided differently.

“Open source” software is defined herein to be source code that allowsdistribution as source code as well as compiled form, with awell-publicized and indexed means of obtaining the source, optionallywith a license that allows modifications and derived works.

The data stores described herein may be any suitable structure (e.g., anactive database, a relational database, a self-referential database, atable, a matrix, an array, a flat file, a documented-oriented storagesystem, a non-relational No-SQL system, and the like), and may becloud-based or otherwise.

As used herein, the term “or” may be construed in either an inclusive orexclusive sense. Moreover, plural instances may be provided forresources, operations, or structures described herein as a singleinstance. Additionally, boundaries between various resources,operations, engines, engines, and data stores are somewhat arbitrary,and particular operations are illustrated in a context of specificillustrative configurations. Other allocations of functionality areenvisioned and may fall within a scope of various embodiments of thepresent disclosure. In general, structures and functionality presentedas separate resources in the example configurations may be implementedas a combined structure or resource. Similarly, structures andfunctionality presented as a single resource may be implemented asseparate resources. These and other variations, modifications,additions, and improvements fall within a scope of embodiments of thepresent disclosure as represented by the appended claims. Thespecification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense.

Conditional language, such as, among others, “can,” “could,” “might,” or“may,” unless specifically stated otherwise, or otherwise understoodwithin the context as used, is generally intended to convey that certainembodiments include, while other embodiments do not include, certainfeatures, elements and/or steps. Thus, such conditional language is notgenerally intended to imply that features, elements and/or steps are inany way required for one or more embodiments or that one or moreembodiments necessarily include logic for deciding, with or without userinput or prompting, whether these features, elements and/or steps areincluded or are to be performed in any particular embodiment.

Although the invention has been described in detail for the purpose ofillustration based on what is currently considered to be the mostpractical and preferred implementations, it is to be understood thatsuch detail is solely for that purpose and that the invention is notlimited to the disclosed implementations, but, on the contrary, isintended to cover modifications and equivalent arrangements that arewithin the spirit and scope of the appended claims. For example, it isto be understood that the present invention contemplates that, to theextent possible, one or more features of any embodiment can be combinedwith one or more features of any other embodiment.

The invention claimed is:
 1. A system for controlling data entrycomprising: one or more processors and a memory storing instructionsthat, when executed by the one or more processors, cause the system to:receive user input from a user defining a data set; define a datacollection construct including a data entry user interface based on theuser input for use in inputting data in the data set; automaticallydefine, according to the defined data collection construct, a schema orindex mappings to generate queries in retrieving data from a datastorage construct that stores data collected through the data collectionconstruct; add a field to or remove a field from the data collectionconstruct; nest the data collection construct having the added orremoved field into a previously defined data collection construct sothat a corresponding field is added or removed from the previouslydefined data collection construct; and apply the schema or the indexmappings to the data storage construct.
 2. The system of claim 1,wherein the system is further caused to: define the queries used toretrieve a portion of the data stored in the data storage constructbased on the defined data collection construct.
 3. The system of claim1, wherein the data collection construct is defined to include a type ofdata in the dataset; and the data storage construct is automaticallydefined based on the type of data and a format to collect data in thedataset.
 4. The system of claim 1, wherein the system is further causedto: determine whether data stored according to the data storageconstruct improperly includes null values.
 5. The system of claim 1,wherein the system is further caused to: automatically modify thedefined schema of the data storage construct based on the modifiedformat of the data collection construct.
 6. The system of claim 1,wherein the system is further caused to: add or remove a field to thedata collection construct; and nest the data collection construct havingthe added or removed field into the previously defined data collectionconstruct so that a corresponding field is added or removed from thepreviously defined data collection construct.
 7. The system of claim 1,wherein the system is further caused to: automatically modify the indexmappings of the data storage construct based on the added or removedfield of the data collection construct.
 8. The system of claim 1,wherein the system is further caused to: control a rate of data transferfrom the datastore to a repository based on a resource constraint orstress associated with the data transfer and a required consistencylevel between the datastore and the repository.
 9. A method implementedby a computing system including one or more physical processors andstorage media storing machine-readable instructions, the methodcomprising: receiving user input from a user defining a data set;defining a data collection construct including: a data entry userinterface based on the user input for use in inputting data in the dataset, and a format, one or more fields, and one or more rules to collectdata in the data set; automatically defining, according to the defineddata collection construct, a schema or index mappings to generatequeries in retrieving data from a data storage construct that storesdata collected through the data collection construct; adding a field tothe data collection construct; nesting the data collection constructhaving the added field into a previously defined data collectionconstruct so that a corresponding field is added from the previouslydefined data collection construct; and applying the schema or the indexmappings to the data storage construct.
 10. The method of claim 9,further comprising: defining the queries used to retrieve a portion ofthe data stored in the data storage construct based on the defined datacollection construct.
 11. The method of claim 9, further comprising:determining whether data stored according to the data storage constructimproperly includes null values.
 12. A non-transitory computer readablemedium comprising instructions that, when executed, cause one or moreprocessors to perform: receiving user input from a user defining a dataset; defining a data collection construct including: a data entry userinterface based on the user input for use in inputting data in the dataset, and a format to collect data in the data set; automaticallydefining, according to the defined data collection construct, a schemaor index mappings to generate queries in retrieving data from a datastorage construct that stores data collected through the data collectionconstruct; modifying the format of the data collection construct;nesting the modified data collection construct into a previously defineddata collection construct so that a same modification is made to thepreviously defined data collection construct; and applying the schema orthe and index mappings to the data storage construct.
 13. Thenon-transitory computer readable medium of claim 12, wherein theinstructions further cause the one or more processors to perform:defining the queries used to retrieve a portion of the data stored inthe data storage construct based on the defined data collectionconstruct.
 14. The non-transitory computer readable medium of claim 12,wherein the instructions further cause the one or more processors toperform: determining whether data stored according to the data storageconstruct improperly includes null values.